UPDATED 22:30 EDT / JUNE 07 2017

BIG DATA

The Machine: Riding the transition wave to the next stage of computing

Traditional computers are powerful, but they have limits. Many technologies are reaching those limits, while the demand for more computing power grows ever greater. The solution is new methods of computing and processing, using new hardware.

Hewlett Packard Enterprise Co. has been on the forefront of research into new computing possibilities, and its work is now bearing fruit, including The Machine, what HPE says is the world’s largest single-memory computer.

“We need the cycle of intelligence, measurement, analysis and action to be microseconds, and that means it needs to happen at the intelligent edge,” said Kirk Bresniker (pictured, right), fellow, vice president and chief architect, HP Labs, at HPE.

Bresniker and his colleague Natalia Vassilieva (pictured, left), senior research manager, HP Labs, at HPE, stopped by theCUBE, SiliconANGLE’s mobile live-streaming studio, at the HPE Discover conference in Las Vegas, Nevada. (* Disclosure below.)

They spoke with theCUBE co-hosts John Furrier (@furrier) and Dave Vellante (@dvellante) about transitional technology, machine learning and The Machine.

Preparing analytics systems for the new data

“One of the things that’s so fascinating about the transitional period we’re in, we look at the kind of technologies we’ve had to date and … are all getting about as good as they’re going to get,” Bresniker said.

They all have a natural life cycle, and they’re maturing. The question, then, is what is coming next?

The kind of applications HPE expects are data-intensive. An individual human can’t analyze that much data, so companies need machine learning to comb through that data for the needles in the haystack, Bresniker explained. With machine learning, companies can discover data relationships that will have a transformational effect.

Recent advances in artificial intelligence are building on this ability. One of those advances is the revival of neural network deep learning, Vassilieva stated. Today, companies are able to train neural nets for tasks like speech recognition, but they want to move forward. To do this, they will need large amounts of data, and processing that much data with traditional computers is nearly impossible, she added.

That’s why HPE is developing The Machine. It’s a processing system that uses a vast, shared memory pool to eliminate the communication bottlenecks between computing nodes. Since all nodes have access to this shared memory, and so don’t have to send data around the system, they can enjoy a significant speed up in processing, Vassilieva stated.

“It will allow us to retrain models on the new data that is coming, and not do training offline anymore,” she said.

Watch the complete video interview below, and be sure to check out more of SiliconANGLE’s and theCUBE’s independent editorial coverage of HPE Discover US 2017(* Disclosure: TheCUBE is a paid media partner for HPE Discover US 2017. Neither Hewlett Packard Enterprise Co. nor other sponsors have editorial control on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE

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